Future SaaS Software Development Trends for SaaS Practitioners' Attention

2023-03-28 11:30:00
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Summary : In recent years, SaaS products have become increasingly popular. With economic recovery and industrial upgrading, what will be the future development of SaaS? This article will elaborate on six aspects of the development trends of SaaS in detail. Let's take a look together with SaaS practitioners or entrepreneurs.

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In the post-pandemic era, the revival of the economy and industrial upgrading has led to increased attention to the characteristics of SaaS in various industries. Consequently, the perception of the value of SaaS has gradually increased, and the payment habits of enterprise users have been cultivated over time.


As SaaS practitioners or entrepreneurs, it is crucial to concentrate on the upcoming trends of SaaS development and explore ways to better align our own SaaS product solutions with these trends for optimal development.

1. Artificial Intelligence (AI)

Currently, AI has become the most popular trend of the day and represents a new generation of SaaS products. We have seen industry giants such as Google, Microsoft, Amazon, and Oracle enter the field with their AI-based products. In 2021, AI technology has made significant advances, leading to a surge in investor interest. With AI applications starting to change traditional industry rules, the projected market value is expected to reach $997.8 billion by 2028.


Efficiency applications, automating large numbers of manual processes, and reducing costs are the most common applications of machine learning in SaaS today. AI provides excellent responsiveness and interaction with users in business scenarios, automating and personalizing services, improving security, and supplementing manpower.


Combining AI and SaaS Product Features:

1) Personalization

AI can provide personalization to SaaS products through natural language processing (NLP) technology, which can automatically handle human voice patterns and voice control. SaaS can deploy AI across customer service functions to address customer needs by personalizing user preferences. For instance, Starbucks' MyStarbucks Barista enables users to make food and beverage reservations and mobile online payments with their voice alone, significantly reducing waiting time in line. Users can interact with the AI online and receive intelligent recommendations based on past user preferences and specific tastes.

2) Speed of Decision Making

AI-enabled SaaS accelerates internal processes and operations, enabling enterprises to obtain quick answers to questions, make predictions, and accelerate response levels. The integration of AI in SaaS products can replace the user in performing routine predictive actions to expedite decision-making operations.

3) Digital Intelligence

The market offers a growing number of excellent SaaS BI data analysis products for enterprises to choose from for data analysis. In the future, SaaS-based data analysis products with artificial intelligence platforms can dynamically conduct analysis to investigate emerging consumer intent, interests, and behaviors in a complex pool of data while integrating valuable data from a variety of sources and segmenting it in a way that provides the best business value.

2. Vertical SaaS

The SaaS industry's development history in both China and the U.S. began with general-purpose products and then progressed to verticals. At present, domestic general-purpose SaaS products comprise roughly two-thirds of the overall industry. Nonetheless, several industry trends suggest that vertical SaaS is becoming increasingly popular in the market, with these solutions tailored to meet industry-specific requirements.


While general products are suitable for the masses, they do not offer enough support for particular industries or scenarios, and the solutions are often uninnovative, resulting in a user experience of "attempting to solve everything, but failing to solve anything."


Vertical SaaS products are typically created by solution providers with extensive industry knowledge and expertise in the specific industry they target. This expertise allows users to enjoy unique process design features and business scenario solutions in their industry.


Vertical SaaS products provide several valuable benefits, including:

  • Business value: Vertical SaaS products are designed to meet the needs of the industry in which they are used and can provide higher degrees of business value to companies in a particular industry by delivering efficient operations and solutions for achieving performance goals.
  • Reasonable data governance: Vertical SaaS products include industry-specific data cleansing rules and compliance features that address data governance procedures. They offer greater transparency of data in upstream and downstream business links and address the problem of information silos in business processes, providing enterprises with more data analysis for decision-making purposes.
  • New niche market: Vertical SaaS aims to solve specific industry pain points, resulting in an upward trend in demand for solutions from business users in the industry. Excellent and advanced vertical SaaS products can quickly open up a new niche market in the industry and accelerate financing progress.
  • Accelerate the construction of enterprise information technology and digitalization: Most enterprises lack a deep understanding of information technology and digitalization and do not adequately consider business scenario solutions. This lack of awareness results in a large number of systems going online or the purchase of several SaaS products, but they are unable to correlate business operation and management through the system. On the other hand, vertical SaaS can quickly bridge the business gap, accelerate information and data interaction, and solve targeted business problems, improving efficiency because it understands the business obstacles and industry pain points faced by enterprises in the corresponding industry.
  • Higher standardization: The reason why more and more enterprises are opting for corresponding vertical SaaS products instead of general-purpose SaaS is that vertical SaaS can provide higher standardization of product solutions and business scenarios. In the future, industry-specific vertical SaaS providers will offer higher quality products and services to meet users' needs and differentiate their products from competitors in the increasingly competitive market, resulting in a large number of innovative niche solutions that will make the whole industry-specific products more standardized and rationalized.

3. Data-Driven SaaS

As digital transformation accelerates in all industries, businesses of all sizes are utilizing big data and analysis to improve their competitiveness and speed up their operations and strategic decisions. This is supported by government information technology and digital policies, and a fiercely competitive marketplace. As a result, there is a growing demand for data analysis of customer behavior, market trends, and additional insights. Enterprises aim to discover business value from data analysis in the long run, and investments in innovation driven by data-driven SaaS are expected to soar. SaaS providers have recognized this opportunity and are continuously developing and releasing powerful business intelligence (BI) tools and platforms. They deliver advanced BI tools with a wide range of capabilities, from centralized dashboards to predictions.


The current generation of data-driven SaaS data products is more centralized in terms of analysis. This enables users to move from single data scenarios to multi-dimensional data analysis, and discover new business insights with dynamic performance data.

4. Machine Learning (ML)

Similar to artificial intelligence, machine learning is expected to achieve significant growth in the SaaS industry in the next few years. As the user's business constantly changes, the scenarios will become increasingly complex, posing challenges for the solutions and functions of SaaS products. Machine learning can make SaaS product solutions more self-improving, thereby improving their operations and intelligence.


Functions such as data pre-processing, facial recognition, data visualization, NLP, predictive and preventive analysis, and deep learning are all based on ML, and in the future, machine learning will be derived from MLaaS (Machine Learning as a Service) along with the product service offerings.

5. API Integration for a Unified SaaS Ecosystem

As businesses expand and evolve, their SaaS solutions can become limited in providing complete solutions for their needs. With the explosive demand for SaaS solutions and their adoption in the market, there is a growing need to integrate multiple SaaS products' solutions into existing business systems. For instance, companies may have already implemented their own supply chain ERP system, and as their business grows, they may require a data analysis product (SaaS BI system) specifically for integrated analysis of business data. However, some SaaS providers may not offer complete integration solutions or their solutions may not be automated and user-friendly.


Some SaaS providers have addressed this issue by redirecting their customers to third-party systems that provide specific APIs to enable customers to integrate the cloud solution into their existing systems. While this approach can address the users' business scenario to some extent, it can lead to reduced user retention. As such, SaaS startups should focus on developing their core competitive product features and rely on third-party APIs to integrate other non-core scenarios for creating complete business scenarios, thereby providing valuable time and resources for early product release.


Currently, more SaaS providers are offering powerful integration features instead of redirecting their customers to third parties. In the future, API integration for a unified SaaS ecosystem will become another major trend in the development of SaaS products, especially in vertical industry sectors where it will be widely used.


If a SaaS provider is functioning with an external provider for API linking, they should address the following questions in advance to ensure that their integration solution meets the needs of their users' business:

  • What features can the external provider offer to my product for integrating SaaS into my existing business system?
  • Is my SaaS data protected during the integration process?
  • Can the provider integrate my old version of the system?

6. Transfer to PaaS

The lack of professional talent and R&D engineers is a significant challenge faced by companies during digital transformation, not only by large enterprises but also by SMEs with limited budgets. To meet this demand for low-cost, tentative SaaS solutions, the growth of the low-code and no-code platform market has rapidly increased.


By using a low-code platform, businesses can speed up the development and deployment of new applications, allowing them to validate internal business process scenarios and increase efficiency. As the SaaS industry evolves and innovative solutions are introduced, many SaaS providers have shifted their focus towards customer retention rather than customer acquisition. In the next three years, we anticipate that SaaS will move further into PaaS (Platform as a Service), which will enable businesses to develop custom applications as add-ons to their original services. Companies like Salesforce and Box have recently released PaaS-focused services to capture a significant share of their niche markets. This SaaS trend is expected to become even more prevalent in the upcoming year.

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